Overview

Dataset statistics

Number of variables13
Number of observations47
Missing cells14
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory110.8 B

Variable types

Text5
Numeric4
Categorical4

Dataset

Description경상북도 영주시 관내 마을회관 현황(주소, 이용인구, 면적 등)
Author경상북도 영주시
URLhttps://www.data.go.kr/data/15044595/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
담당자연락처 is highly overall correlated with 이용인구(명) and 1 other fieldsHigh correlation
담당자소속 is highly overall correlated with 이용인구(명) and 1 other fieldsHigh correlation
이용인구(명) is highly overall correlated with 담당자소속 and 1 other fieldsHigh correlation
연면적(㎡) is highly overall correlated with 건축면적(㎡)High correlation
건축면적(㎡) is highly overall correlated with 연면적(㎡)High correlation
마을명칭(자연부락) has 14 (29.8%) missing valuesMissing
명칭 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
소재지지번주소 has unique valuesUnique
연면적(㎡) has unique valuesUnique
건축면적(㎡) has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:20:46.965221
Analysis finished2023-12-12 09:20:50.208864
Duration3.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

명칭
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-12T18:20:50.413663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length8.7659574
Min length5

Characters and Unicode

Total characters412
Distinct characters65
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row성내1리 마을회관
2nd row성내2리 마을회관
3rd row성내3리 마을회관
4th row성내4리 새마을회관
5th row동부1리 마을회관
ValueCountFrequency (%)
마을회관 38
42.7%
새마을회관 3
 
3.4%
금계1리 2
 
2.2%
성내1리 1
 
1.1%
만방1리 1
 
1.1%
용산1리 1
 
1.1%
단촌1리 1
 
1.1%
오계1리 1
 
1.1%
봉암리 1
 
1.1%
내줄리 1
 
1.1%
Other values (39) 39
43.8%
2023-12-12T18:20:50.839972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 47
11.4%
을 47
11.4%
관 47
11.4%
회 46
11.2%
42
10.2%
리 40
9.7%
1 19
 
4.6%
2 13
 
3.2%
부 6
 
1.5%
동 6
 
1.5%
Other values (55) 99
24.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
80.1%
Space Separator 42
 
10.2%
Decimal Number 38
 
9.2%
Uppercase Letter 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 47
14.2%
을 47
14.2%
관 47
14.2%
회 46
13.9%
리 40
12.1%
부 6
 
1.8%
동 6
 
1.8%
내 5
 
1.5%
산 5
 
1.5%
성 4
 
1.2%
Other values (46) 77
23.3%
Decimal Number
ValueCountFrequency (%)
1 19
50.0%
2 13
34.2%
3 3
 
7.9%
5 1
 
2.6%
4 1
 
2.6%
6 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
80.1%
Common 80
 
19.4%
Latin 2
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 47
14.2%
을 47
14.2%
관 47
14.2%
회 46
13.9%
리 40
12.1%
부 6
 
1.8%
동 6
 
1.8%
내 5
 
1.5%
산 5
 
1.5%
성 4
 
1.2%
Other values (46) 77
23.3%
Common
ValueCountFrequency (%)
42
52.5%
1 19
23.8%
2 13
 
16.2%
3 3
 
3.8%
5 1
 
1.2%
4 1
 
1.2%
6 1
 
1.2%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
80.1%
ASCII 82
 
19.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 47
14.2%
을 47
14.2%
관 47
14.2%
회 46
13.9%
리 40
12.1%
부 6
 
1.8%
동 6
 
1.8%
내 5
 
1.5%
산 5
 
1.5%
성 4
 
1.2%
Other values (46) 77
23.3%
ASCII
ValueCountFrequency (%)
42
51.2%
1 19
23.2%
2 13
 
15.9%
3 3
 
3.7%
5 1
 
1.2%
4 1
 
1.2%
6 1
 
1.2%
S 1
 
1.2%
K 1
 
1.2%

소재지도로명주소
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-12T18:20:51.155965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length23.148936
Min length18

Characters and Unicode

Total characters1088
Distinct characters83
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row경상북도 영주시 풍기읍 기주로 132
2nd row경상북도 영주시 풍기읍 기주로 88-6
3rd row경상북도 영주시 풍기읍 남원로 86-8
4th row경상북도 영주시 풍기읍 남원로 112
5th row경상북도 영주시 풍기읍 기주로65번길 5
ValueCountFrequency (%)
경상북도 47
20.0%
영주시 47
20.0%
풍기읍 18
 
7.7%
부석면 6
 
2.6%
안정면 5
 
2.1%
33 4
 
1.7%
단산면 4
 
1.7%
이산면 3
 
1.3%
8 2
 
0.9%
평은면 2
 
0.9%
Other values (90) 97
41.3%
2023-12-12T18:20:51.604444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
17.3%
주 54
 
5.0%
영 51
 
4.7%
상 50
 
4.6%
경 47
 
4.3%
북 47
 
4.3%
도 47
 
4.3%
시 47
 
4.3%
1 45
 
4.1%
로 44
 
4.0%
Other values (73) 468
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
61.9%
Decimal Number 207
 
19.0%
Space Separator 188
 
17.3%
Dash Punctuation 15
 
1.4%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 54
 
8.0%
영 51
 
7.6%
상 50
 
7.4%
경 47
 
7.0%
북 47
 
7.0%
도 47
 
7.0%
시 47
 
7.0%
로 44
 
6.5%
길 34
 
5.0%
번 31
 
4.6%
Other values (59) 222
32.9%
Decimal Number
ValueCountFrequency (%)
1 45
21.7%
3 28
13.5%
2 22
10.6%
5 22
10.6%
7 18
 
8.7%
9 16
 
7.7%
4 14
 
6.8%
8 14
 
6.8%
6 14
 
6.8%
0 14
 
6.8%
Space Separator
ValueCountFrequency (%)
188
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 674
61.9%
Common 414
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 54
 
8.0%
영 51
 
7.6%
상 50
 
7.4%
경 47
 
7.0%
북 47
 
7.0%
도 47
 
7.0%
시 47
 
7.0%
로 44
 
6.5%
길 34
 
5.0%
번 31
 
4.6%
Other values (59) 222
32.9%
Common
ValueCountFrequency (%)
188
45.4%
1 45
 
10.9%
3 28
 
6.8%
2 22
 
5.3%
5 22
 
5.3%
7 18
 
4.3%
9 16
 
3.9%
- 15
 
3.6%
4 14
 
3.4%
8 14
 
3.4%
Other values (4) 32
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 674
61.9%
ASCII 414
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
45.4%
1 45
 
10.9%
3 28
 
6.8%
2 22
 
5.3%
5 22
 
5.3%
7 18
 
4.3%
9 16
 
3.9%
- 15
 
3.6%
4 14
 
3.4%
8 14
 
3.4%
Other values (4) 32
 
7.7%
Hangul
ValueCountFrequency (%)
주 54
 
8.0%
영 51
 
7.6%
상 50
 
7.4%
경 47
 
7.0%
북 47
 
7.0%
도 47
 
7.0%
시 47
 
7.0%
로 44
 
6.5%
길 34
 
5.0%
번 31
 
4.6%
Other values (59) 222
32.9%

소재지지번주소
Text

UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-12T18:20:52.011317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length22.085106
Min length18

Characters and Unicode

Total characters1038
Distinct characters78
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)100.0%

Sample

1st row경상북도 영주시 풍기읍 성내1리 182-3
2nd row경상북도 영주시 풍기읍 성내2리 10-1
3rd row경상북도 영주시 풍기읍 성내3리 102-5
4th row경상북도 영주시 풍기읍 성내4리 123-1
5th row경상북도 영주시 풍기읍 동부1리 528
ValueCountFrequency (%)
경상북도 47
20.2%
영주시 47
20.2%
풍기읍 18
 
7.7%
부석면 6
 
2.6%
안정면 5
 
2.1%
단산면 4
 
1.7%
이산면 3
 
1.3%
용상리 2
 
0.9%
문수면 2
 
0.9%
평은면 2
 
0.9%
Other values (94) 97
41.6%
2023-12-12T18:20:52.600175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
186
17.9%
상 50
 
4.8%
1 48
 
4.6%
주 47
 
4.5%
시 47
 
4.5%
경 47
 
4.5%
영 47
 
4.5%
북 47
 
4.5%
도 47
 
4.5%
리 45
 
4.3%
Other values (68) 427
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 602
58.0%
Decimal Number 210
 
20.2%
Space Separator 186
 
17.9%
Dash Punctuation 40
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 50
 
8.3%
주 47
 
7.8%
시 47
 
7.8%
경 47
 
7.8%
영 47
 
7.8%
북 47
 
7.8%
도 47
 
7.8%
리 45
 
7.5%
면 27
 
4.5%
읍 18
 
3.0%
Other values (56) 180
29.9%
Decimal Number
ValueCountFrequency (%)
1 48
22.9%
2 35
16.7%
3 27
12.9%
4 18
 
8.6%
6 16
 
7.6%
0 15
 
7.1%
8 14
 
6.7%
7 14
 
6.7%
5 14
 
6.7%
9 9
 
4.3%
Space Separator
ValueCountFrequency (%)
186
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 602
58.0%
Common 436
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 50
 
8.3%
주 47
 
7.8%
시 47
 
7.8%
경 47
 
7.8%
영 47
 
7.8%
북 47
 
7.8%
도 47
 
7.8%
리 45
 
7.5%
면 27
 
4.5%
읍 18
 
3.0%
Other values (56) 180
29.9%
Common
ValueCountFrequency (%)
186
42.7%
1 48
 
11.0%
- 40
 
9.2%
2 35
 
8.0%
3 27
 
6.2%
4 18
 
4.1%
6 16
 
3.7%
0 15
 
3.4%
8 14
 
3.2%
7 14
 
3.2%
Other values (2) 23
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 602
58.0%
ASCII 436
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
186
42.7%
1 48
 
11.0%
- 40
 
9.2%
2 35
 
8.0%
3 27
 
6.2%
4 18
 
4.1%
6 16
 
3.7%
0 15
 
3.4%
8 14
 
3.2%
7 14
 
3.2%
Other values (2) 23
 
5.3%
Hangul
ValueCountFrequency (%)
상 50
 
8.3%
주 47
 
7.8%
시 47
 
7.8%
경 47
 
7.8%
영 47
 
7.8%
북 47
 
7.8%
도 47
 
7.8%
리 45
 
7.5%
면 27
 
4.5%
읍 18
 
3.0%
Other values (56) 180
29.9%

마을명칭(자연부락)
Text

MISSING 

Distinct33
Distinct (%)100.0%
Missing14
Missing (%)29.8%
Memory size508.0 B
2023-12-12T18:20:52.871437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.5454545
Min length2

Characters and Unicode

Total characters84
Distinct characters62
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)100.0%

Sample

1st row공원산
2nd row쇠바리
3rd row히여골
4th row속계
5th row새터
ValueCountFrequency (%)
문화마을 1
 
3.0%
오계1리 1
 
3.0%
봉암 1
 
3.0%
내줄 1
 
3.0%
엄고개 1
 
3.0%
소미마을 1
 
3.0%
먹골 1
 
3.0%
야동 1
 
3.0%
회석 1
 
3.0%
공원산 1
 
3.0%
Other values (23) 23
69.7%
2023-12-12T18:20:53.358816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
골 4
 
4.8%
마 3
 
3.6%
을 3
 
3.6%
암 3
 
3.6%
1 3
 
3.6%
계 3
 
3.6%
산 3
 
3.6%
문 2
 
2.4%
용 2
 
2.4%
리 2
 
2.4%
Other values (52) 56
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81
96.4%
Decimal Number 3
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
골 4
 
4.9%
마 3
 
3.7%
을 3
 
3.7%
암 3
 
3.7%
계 3
 
3.7%
산 3
 
3.7%
문 2
 
2.5%
용 2
 
2.5%
리 2
 
2.5%
고 2
 
2.5%
Other values (51) 54
66.7%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81
96.4%
Common 3
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
골 4
 
4.9%
마 3
 
3.7%
을 3
 
3.7%
암 3
 
3.7%
계 3
 
3.7%
산 3
 
3.7%
문 2
 
2.5%
용 2
 
2.5%
리 2
 
2.5%
고 2
 
2.5%
Other values (51) 54
66.7%
Common
ValueCountFrequency (%)
1 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81
96.4%
ASCII 3
 
3.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
골 4
 
4.9%
마 3
 
3.7%
을 3
 
3.7%
암 3
 
3.7%
계 3
 
3.7%
산 3
 
3.7%
문 2
 
2.5%
용 2
 
2.5%
리 2
 
2.5%
고 2
 
2.5%
Other values (51) 54
66.7%
ASCII
ValueCountFrequency (%)
1 3
100.0%

이용인구(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)48.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.382979
Minimum15
Maximum227
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T18:20:53.529631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile20
Q132
median42
Q350
95-th percentile148.5
Maximum227
Range212
Interquartile range (IQR)18

Descriptive statistics

Standard deviation44.14529
Coefficient of variation (CV)0.76930984
Kurtosis4.1956335
Mean57.382979
Median Absolute Deviation (MAD)8
Skewness1.97243
Sum2697
Variance1948.8067
MonotonicityNot monotonic
2023-12-12T18:20:53.682358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
40 7
14.9%
50 6
12.8%
20 6
12.8%
45 3
 
6.4%
30 3
 
6.4%
15 2
 
4.3%
41 2
 
4.3%
90 2
 
4.3%
42 2
 
4.3%
34 1
 
2.1%
Other values (13) 13
27.7%
ValueCountFrequency (%)
15 2
 
4.3%
20 6
12.8%
28 1
 
2.1%
30 3
6.4%
34 1
 
2.1%
36 1
 
2.1%
40 7
14.9%
41 2
 
4.3%
42 2
 
4.3%
43 1
 
2.1%
ValueCountFrequency (%)
227 1
2.1%
162 1
2.1%
159 1
2.1%
124 1
2.1%
120 1
2.1%
112 1
2.1%
110 1
2.1%
98 1
2.1%
95 1
2.1%
90 2
4.3%

건립연도
Real number (ℝ)

Distinct24
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2003.0638
Minimum1970
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T18:20:53.859317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1970
5-th percentile1972
Q11999
median2005
Q32013
95-th percentile2016
Maximum2019
Range49
Interquartile range (IQR)14

Descriptive statistics

Standard deviation12.850993
Coefficient of variation (CV)0.006415668
Kurtosis1.4924805
Mean2003.0638
Median Absolute Deviation (MAD)7
Skewness-1.4217458
Sum94144
Variance165.14801
MonotonicityNot monotonic
2023-12-12T18:20:54.057097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2004 5
 
10.6%
2013 4
 
8.5%
2016 3
 
6.4%
2009 3
 
6.4%
2011 3
 
6.4%
1996 3
 
6.4%
2014 3
 
6.4%
2005 2
 
4.3%
2002 2
 
4.3%
2006 2
 
4.3%
Other values (14) 17
36.2%
ValueCountFrequency (%)
1970 2
4.3%
1972 2
4.3%
1976 1
 
2.1%
1987 1
 
2.1%
1995 1
 
2.1%
1996 3
6.4%
1998 1
 
2.1%
1999 2
4.3%
2001 1
 
2.1%
2002 2
4.3%
ValueCountFrequency (%)
2019 1
 
2.1%
2017 1
 
2.1%
2016 3
6.4%
2015 1
 
2.1%
2014 3
6.4%
2013 4
8.5%
2011 3
6.4%
2009 3
6.4%
2008 1
 
2.1%
2007 1
 
2.1%

연면적(㎡)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean114.46511
Minimum23.14
Maximum208.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T18:20:54.250715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.14
5-th percentile41.04
Q182.8
median101.4
Q3145.245
95-th percentile195.991
Maximum208.44
Range185.3
Interquartile range (IQR)62.445

Descriptive statistics

Standard deviation48.75945
Coefficient of variation (CV)0.42597654
Kurtosis-0.72362814
Mean114.46511
Median Absolute Deviation (MAD)34.29
Skewness0.3353587
Sum5379.86
Variance2377.484
MonotonicityNot monotonic
2023-12-12T18:20:54.466099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
23.14 1
 
2.1%
140.73 1
 
2.1%
197.35 1
 
2.1%
89.45 1
 
2.1%
34.2 1
 
2.1%
191.4 1
 
2.1%
82.3 1
 
2.1%
88.56 1
 
2.1%
141.57 1
 
2.1%
95.78 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
23.14 1
2.1%
34.2 1
2.1%
39.6 1
2.1%
44.4 1
2.1%
63.43 1
2.1%
66.0 1
2.1%
66.3 1
2.1%
71.76 1
2.1%
72.73 1
2.1%
74.64 1
2.1%
ValueCountFrequency (%)
208.44 1
2.1%
205.04 1
2.1%
197.35 1
2.1%
192.82 1
2.1%
191.71 1
2.1%
191.4 1
2.1%
189.47 1
2.1%
183.36 1
2.1%
156.58 1
2.1%
153.07 1
2.1%

건축면적(㎡)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct47
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.454362
Minimum23.14
Maximum208.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size555.0 B
2023-12-12T18:20:54.675791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.14
5-th percentile41.037
Q171.51
median91.2
Q3113.11
95-th percentile152.952
Maximum208.44
Range185.3
Interquartile range (IQR)41.6

Descriptive statistics

Standard deviation35.63994
Coefficient of variation (CV)0.37732444
Kurtosis1.2781926
Mean94.454362
Median Absolute Deviation (MAD)20.91
Skewness0.57641278
Sum4439.355
Variance1270.2053
MonotonicityNot monotonic
2023-12-12T18:20:54.885078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
23.14 1
 
2.1%
144.93 1
 
2.1%
96.75 1
 
2.1%
95.42 1
 
2.1%
34.2 1
 
2.1%
97.5 1
 
2.1%
87.93 1
 
2.1%
88.56 1
 
2.1%
116.9 1
 
2.1%
44.39 1
 
2.1%
Other values (37) 37
78.7%
ValueCountFrequency (%)
23.14 1
2.1%
34.2 1
2.1%
39.6 1
2.1%
44.39 1
2.1%
44.4 1
2.1%
45.01 1
2.1%
63.43 1
2.1%
63.5 1
2.1%
66.0 1
2.1%
66.15 1
2.1%
ValueCountFrequency (%)
208.44 1
2.1%
162.86 1
2.1%
156.39 1
2.1%
144.93 1
2.1%
134.945 1
2.1%
133.6 1
2.1%
129.12 1
2.1%
128.12 1
2.1%
117.86 1
2.1%
117.84 1
2.1%

담당자소속
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
풍기읍
18 
부석면
6 
안정면
5 
단산면
4 
이산면
3 
Other values (7)
11 

Length

Max length4
Median length3
Mean length3.0425532
Min length3

Unique

Unique3 ?
Unique (%)6.4%

Sample

1st row풍기읍
2nd row풍기읍
3rd row풍기읍
4th row풍기읍
5th row풍기읍

Common Values

ValueCountFrequency (%)
풍기읍 18
38.3%
부석면 6
 
12.8%
안정면 5
 
10.6%
단산면 4
 
8.5%
이산면 3
 
6.4%
평은면 2
 
4.3%
문수면 2
 
4.3%
봉현면 2
 
4.3%
순흥면 2
 
4.3%
장수면 1
 
2.1%
Other values (2) 2
 
4.3%

Length

2023-12-12T18:20:55.084466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
풍기읍 18
38.3%
부석면 6
 
12.8%
안정면 5
 
10.6%
단산면 4
 
8.5%
이산면 3
 
6.4%
평은면 2
 
4.3%
문수면 2
 
4.3%
봉현면 2
 
4.3%
순흥면 2
 
4.3%
장수면 1
 
2.1%
Other values (2) 2
 
4.3%

담당자연락처
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)25.5%
Missing0
Missing (%)0.0%
Memory size508.0 B
054-639-7405
18 
054-639-7705
6 
054-639-7566
5 
054-639-7665
4 
054-639-7451
3 
Other values (7)
11 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique3 ?
Unique (%)6.4%

Sample

1st row054-639-7405
2nd row054-639-7405
3rd row054-639-7405
4th row054-639-7405
5th row054-639-7405

Common Values

ValueCountFrequency (%)
054-639-7405 18
38.3%
054-639-7705 6
 
12.8%
054-639-7566 5
 
10.6%
054-639-7665 4
 
8.5%
054-639-7451 3
 
6.4%
054-639-7474 2
 
4.3%
054-639-7504 2
 
4.3%
054-639-7605 2
 
4.3%
054-639-7634 2
 
4.3%
054-639-7535 1
 
2.1%
Other values (2) 2
 
4.3%

Length

2023-12-12T18:20:55.225545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
054-639-7405 18
38.3%
054-639-7705 6
 
12.8%
054-639-7566 5
 
10.6%
054-639-7665 4
 
8.5%
054-639-7451 3
 
6.4%
054-639-7474 2
 
4.3%
054-639-7504 2
 
4.3%
054-639-7605 2
 
4.3%
054-639-7634 2
 
4.3%
054-639-7535 1
 
2.1%
Other values (2) 2
 
4.3%

등기여부
Categorical

Distinct6
Distinct (%)12.8%
Missing0
Missing (%)0.0%
Memory size508.0 B
마을회
16 
새마을회
12 
여
10 
부
6 
영주시
2 

Length

Max length4
Median length3
Mean length2.5744681
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row부
2nd row여
3rd row여
4th row새마을회
5th row여

Common Values

ValueCountFrequency (%)
마을회 16
34.0%
새마을회 12
25.5%
여 10
21.3%
부 6
 
12.8%
영주시 2
 
4.3%
조기환 1
 
2.1%

Length

2023-12-12T18:20:55.388247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:55.548446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을회 16
34.0%
새마을회 12
25.5%
여 10
21.3%
부 6
 
12.8%
영주시 2
 
4.3%
조기환 1
 
2.1%

대표자
Text

Distinct46
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size508.0 B
2023-12-12T18:20:55.832915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length3
Mean length4.0212766
Min length3

Characters and Unicode

Total characters189
Distinct characters83
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)95.7%

Sample

1st row한명순
2nd row서석수
3rd row김용갑
4th row김도진
5th row권우섭
ValueCountFrequency (%)
이승철 2
 
4.3%
김진환 1
 
2.1%
박홍식 1
 
2.1%
이재학 1
 
2.1%
단촌1리새마을회 1
 
2.1%
오계1리새마을회 1
 
2.1%
봉암리새마을회 1
 
2.1%
내줄동새마을회 1
 
2.1%
정효진 1
 
2.1%
박재열 1
 
2.1%
Other values (36) 36
76.6%
2023-12-12T18:20:56.292553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 13
 
6.9%
회 9
 
4.8%
마 8
 
4.2%
을 8
 
4.2%
이 7
 
3.7%
박 6
 
3.2%
새 6
 
3.2%
리 6
 
3.2%
진 5
 
2.6%
1 4
 
2.1%
Other values (73) 117
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 184
97.4%
Decimal Number 5
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 13
 
7.1%
회 9
 
4.9%
마 8
 
4.3%
을 8
 
4.3%
이 7
 
3.8%
박 6
 
3.3%
새 6
 
3.3%
리 6
 
3.3%
진 5
 
2.7%
용 4
 
2.2%
Other values (71) 112
60.9%
Decimal Number
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 184
97.4%
Common 5
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 13
 
7.1%
회 9
 
4.9%
마 8
 
4.3%
을 8
 
4.3%
이 7
 
3.8%
박 6
 
3.3%
새 6
 
3.3%
리 6
 
3.3%
진 5
 
2.7%
용 4
 
2.2%
Other values (71) 112
60.9%
Common
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 184
97.4%
ASCII 5
 
2.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 13
 
7.1%
회 9
 
4.9%
마 8
 
4.3%
을 8
 
4.3%
이 7
 
3.8%
박 6
 
3.3%
새 6
 
3.3%
리 6
 
3.3%
진 5
 
2.7%
용 4
 
2.2%
Other values (71) 112
60.9%
ASCII
ValueCountFrequency (%)
1 4
80.0%
2 1
 
20.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size508.0 B
2017-05-12
47 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017-05-12
2nd row2017-05-12
3rd row2017-05-12
4th row2017-05-12
5th row2017-05-12

Common Values

ValueCountFrequency (%)
2017-05-12 47
100.0%

Length

2023-12-12T18:20:56.483189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:20:56.615577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017-05-12 47
100.0%

Interactions

2023-12-12T18:20:49.450463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:47.698663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.151685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.963238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.544220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:47.791162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.265793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.072607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.658845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:47.901005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.378738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.195302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.764208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.019584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:48.504462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:20:49.305535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:20:56.706331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
명칭소재지도로명주소소재지지번주소마을명칭(자연부락)이용인구(명)건립연도연면적(㎡)건축면적(㎡)담당자소속담당자연락처등기여부대표자
명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
마을명칭(자연부락)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
이용인구(명)1.0001.0001.0001.0001.0000.0000.0000.2960.8590.8590.0001.000
건립연도1.0001.0001.0001.0000.0001.0000.6990.4900.1590.1590.4791.000
연면적(㎡)1.0001.0001.0001.0000.0000.6991.0000.8190.2610.2610.6960.975
건축면적(㎡)1.0001.0001.0001.0000.2960.4900.8191.0000.6560.6560.3820.976
담당자소속1.0001.0001.0001.0000.8590.1590.2610.6561.0001.0000.0001.000
담당자연락처1.0001.0001.0001.0000.8590.1590.2610.6561.0001.0000.0001.000
등기여부1.0001.0001.0001.0000.0000.4790.6960.3820.0000.0001.0000.911
대표자1.0001.0001.0001.0001.0001.0000.9750.9761.0001.0000.9111.000
2023-12-12T18:20:56.895253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
담당자연락처담당자소속등기여부
담당자연락처1.0001.0000.000
담당자소속1.0001.0000.000
등기여부0.0000.0001.000
2023-12-12T18:20:57.015400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용인구(명)건립연도연면적(㎡)건축면적(㎡)담당자소속담당자연락처등기여부
이용인구(명)1.0000.1870.0760.1730.6080.6080.000
건립연도0.1871.0000.2770.3320.1370.1370.181
연면적(㎡)0.0760.2771.0000.7340.0750.0750.433
건축면적(㎡)0.1730.3320.7341.0000.3270.3270.183
담당자소속0.6080.1370.0750.3271.0001.0000.000
담당자연락처0.6080.1370.0750.3271.0001.0000.000
등기여부0.0000.1810.4330.1830.0000.0001.000

Missing values

2023-12-12T18:20:49.927539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:20:50.121415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

명칭소재지도로명주소소재지지번주소마을명칭(자연부락)이용인구(명)건립연도연면적(㎡)건축면적(㎡)담당자소속담당자연락처등기여부대표자데이터기준일자
0성내1리 마을회관경상북도 영주시 풍기읍 기주로 132경상북도 영주시 풍기읍 성내1리 182-3<NA>45197023.1423.14풍기읍054-639-7405부한명순2017-05-12
1성내2리 마을회관경상북도 영주시 풍기읍 기주로 88-6경상북도 영주시 풍기읍 성내2리 10-1<NA>402009140.73144.93풍기읍054-639-7405여서석수2017-05-12
2성내3리 마을회관경상북도 영주시 풍기읍 남원로 86-8경상북도 영주시 풍기읍 성내3리 102-5<NA>43197272.7372.73풍기읍054-639-7405여김용갑2017-05-12
3성내4리 새마을회관경상북도 영주시 풍기읍 남원로 112경상북도 영주시 풍기읍 성내4리 123-1<NA>502006189.47129.12풍기읍054-639-7405새마을회김도진2017-05-12
4동부1리 마을회관경상북도 영주시 풍기읍 기주로65번길 5경상북도 영주시 풍기읍 동부1리 528<NA>452014156.5870.29풍기읍054-639-7405여권우섭2017-05-12
5동부2리 새마을회관경상북도 영주시 풍기읍 기주로60번길 33경상북도 영주시 풍기읍 동부2리 436-4<NA>422009183.36162.86풍기읍054-639-7405새마을회정순진2017-05-12
6동부6리 마을회관경상북도 영주시 풍기읍 동성로70번길 17-12경상북도 영주시 풍기읍 동부6리 400-7<NA>28197663.4363.43풍기읍054-639-7405여황병도2017-05-12
7금계1리 공원산 마을회관경상북도 영주시 풍기읍 기주로170번길 58경상북도 영주시 풍기읍 금계1리 398-1공원산20201382.3588.29풍기읍054-639-7405마을회이승철2017-05-12
8금계1리 마을회관경상북도 영주시 풍기읍 무릉길2번길 37경상북도 영주시 풍기읍 금계1리 567쇠바리30197066.066.0풍기읍054-639-7405부이승철2017-05-12
9서부1리 마을회관경상북도 영주시 풍기읍 동성로94번길 20-14경상북도 영주시 풍기읍 서부1리 105-5<NA>342005135.26109.56풍기읍054-639-7405마을회김동호2017-05-12
명칭소재지도로명주소소재지지번주소마을명칭(자연부락)이용인구(명)건립연도연면적(㎡)건축면적(㎡)담당자소속담당자연락처등기여부대표자데이터기준일자
37사천1리 마을회관경상북도 영주시 단산면 단산로115번길 4-13경상북도 영주시 단산면 사천1리 458-4사천90199584.2184.21단산면054-639-7665부조승덕2017-05-12
38구구2리 마을회관경상북도 영주시 단산면 구구로105번길 19-2경상북도 영주시 단산면 구구2리 679-2<NA>202006153.0745.01단산면054-639-7665새마을회서석열2017-05-12
39광창 마을회관경상북도 영주시 부석면 보계로 9경상북도 영주시 부석면 보계1리 179-3광창402003108.06114.42부석면054-639-7705마을회박영박2017-05-12
40소천5리 마을회관경상북도 영주시 부석면 사문로 162경상북도 영주시 부석면 소천5리 673-1사문302004101.66108.02부석면054-639-7705마을회김종호2017-05-12
41감곡2리 마을회관경상북도 영주시 부석면 동원로 693-1경상북도 영주시 부석면 감곡2리 184-12영모암20200296.3102.66부석면054-639-7705마을회임영선2017-05-12
42임곡1리 마을회관경상북도 영주시 부석면 영부로117번길 76-9경상북도 영주시 부석면 임곡1리 612-3고마을40201466.366.3부석면054-639-7705마을회김원상2017-05-12
43임곡2리 마을회관경상북도 영주시 부석면 영부로106번길 13경상북도 영주시 부석면 임곡리 350-2<NA>1102016101.4111.8부석면054-639-7705마을회이운형2017-05-12
44명암정 마을회관경상북도 영주시 부석면 의상로1522번길 51경상북도 영주시 부석면 우곡리 170-6명암정40201671.7666.15부석면054-639-7705마을회김덕수2017-05-12
45조암동회관경상북도 영주시 조암로43번길 271-3 (조암동)경상북도 영주시 조암동 726-2노현227201474.6476.64휴천3동054-639-7931마을회박홍식2017-05-12
46필두마을SK화합관경상북도 영주시 필두길 58 (상줄동)경상북도 영주시 상줄동 106-1<NA>1202016208.44208.44가흥2동054-639-7973마을회박성준2017-05-12